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Open-Domain Question Answering

Open-domain question answering is the task of question answering on open-domain datasets such as Wikipedia.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–10 of 494 papers

Title	Date	Tasks	Status	Hype
TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning	Jun 12, 2025	Answer GenerationChunking	CodeCode Available	2
Efficient Context Selection for Long-Context QA: No Tuning, No Iteration, Just Adaptive-k	Jun 10, 2025	Open-Domain Question AnsweringQuestion Answering	—Unverified	0
ECoRAG: Evidentiality-guided Compression for Long Context RAG	Jun 5, 2025	Answer GenerationOpen-Domain Question Answering	CodeCode Available	1
GenKI: Enhancing Open-Domain Question Answering with Knowledge Integration and Controllable Generation in Large Language Models	May 26, 2025	Open-Domain Question AnsweringPassage Retrieval	CodeCode Available	0
NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning	May 21, 2025	General Reinforcement LearningLogical Reasoning	CodeCode Available	1
Single LLM, Multiple Roles: A Unified Retrieval-Augmented Generation Framework Using Role-Specific Token Optimization	May 21, 2025	Open-Domain Question AnsweringQuestion Answering	—Unverified	0
Unveiling Knowledge Utilization Mechanisms in LLM-based Retrieval-Augmented Generation	May 17, 2025	Open-Domain Question AnsweringQuestion Answering	—Unverified	0
Scaling Reasoning can Improve Factuality in Large Language Models	May 16, 2025	Knowledge GraphsLarge Language Model	CodeCode Available	0
Benchmarking LLM-based Relevance Judgment Methods	Apr 17, 2025	BenchmarkingOpen-Domain Question Answering	CodeCode Available	0
Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Task	Apr 4, 2025	Open-Domain Question AnsweringQuestion Answering	—Unverified	0

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All datasets KILT: ELI5 KILT: Natural Questions KILT: TriviaQA KILT: HotpotQA SearchQA ELI5 QUASAR Natural Questions SQuAD1.1 dev WebQuestions SQuAD1.1 DuReader

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SpanBERT	F1	84.8	—	Unverified
2	Cluster-Former (#C=512)	EM	68	—	Unverified
3	Locality-Sensitive Hashing	EM	66	—	Unverified
4	Multi-passage BERT	EM	65.1	—	Unverified
5	Sparse Attention	EM	64.7	—	Unverified
6	DECAPROP	EM	62.2	—	Unverified
7	Bi-Attention + DCU-LSTM	N-gram F1	59.5	—	Unverified
8	Denoising QA	EM	58.8	—	Unverified
9	DecaProp	EM	56.8	—	Unverified
10	AMANDA	N-gram F1	56.6	—	Unverified